Ontology-Based Data Access and Integration

Living reference work entry
DOI: https://doi.org/10.1007/978-1-4899-7993-3_80667-1

Definition

An ontology-based data integration(OBDI) system is an information management system consisting of three components: an ontology, a set of data sources, and the mapping between the two. The ontology is a conceptual, formal description of the domain of interest to a given organization (or a community of users), expressed in terms of relevant concepts, attributes of concepts, relationships between concepts, and logical assertions characterizing the domain knowledge. The data sources are the repositories accessible by the organization where data concerning the domain are stored. In the general case, such repositories are numerous, heterogeneous, each one managed and maintained independently from the others. The mapping is a precise specification of the correspondence between the data contained in the data sources and the elements of the ontology. The main purpose of an OBDI system is to allow information consumers to query the data using the elements in the ontology as...

Keywords

Ontology-based Data Integration (OBDI) Union Of Conjunctive Queries (UCQ) OBDI System Query Rewriting Mapping Assertions 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Recommended Reading

  1. 1.
    Baader F, Calvanese D, McGuinness D, Nardi D, Patel-Schneider PF, editors. The description logic handbook: theory, implementation and applications. 2nd ed. Cambridge: Cambridge University Press; 2007.zbMATHGoogle Scholar
  2. 2.
    Calì A, Gottlob G, Lukasiewicz T. A general datalog-based framework for tractable query answering over ontologies. J Web Semant. 2012;14:57–83.CrossRefGoogle Scholar
  3. 3.
    Calvanese D, De Giacomo G, Lembo D, Lenzerini M, Rosati R. Tractable reasoning and efficient query answering in description logics: the DL-Lite family. J Autom Reason. 2007;39(3):385–429.MathSciNetCrossRefzbMATHGoogle Scholar
  4. 4.
    Ceri S, Gottlob G, Tanca L. Logic programming and databases. Berlin: Springer; 1990.CrossRefGoogle Scholar
  5. 5.
    Chortaras A, Trivela D, Stamou GB. Optimized query rewriting for OWL 2 QL. In: Proceeding of the 23rd international conference on automated deduction (CADE). Wroclaw; 2011. p. 192–206.Google Scholar
  6. 6.
    Eiter T, Ortiz M, Simkus M, Tran T-K, Xiao G. Query rewriting for Horn-SHIQ plus rules. In: Proceeding of the 26th AAAI conference on artificial intelligence (AAAI). Toronto: AAAI Press; 2012.Google Scholar
  7. 7.
    Gottlob G, Kikot S, Kontchakov R, Podolskii VV, Schwentick T, Zakharyaschev M. The price of query rewriting in ontology-based data access. Artif Intell. 2014;213:42–59.MathSciNetCrossRefzbMATHGoogle Scholar
  8. 8.
    Imielinski T, Lipski W Jr. Incomplete information in relational databases. J ACM. 1984;31(4):761–91.MathSciNetCrossRefzbMATHGoogle Scholar
  9. 9.
    Kontchakov R, Lutz C, Toman D, Wolter F, Zakharyaschev M. The combined approach to ontology-based data access. In: Proceeding of the 22nd international joint conference on artificial intelligence (IJCAI). Barcelona; 2011. p. 2656–61.Google Scholar
  10. 10.
    Leitsch A. The resolution calculus. Berlin: Springer; 1997.CrossRefzbMATHGoogle Scholar
  11. 11.
    Lenzerini M. Data integration: a theoretical perspective. In: Proceeding of the 21st ACM symposium on principles of database systems (PODS). Madison; 2002. p. 233–46.Google Scholar
  12. 12.
    Levy AY, Rousset M-C. Combining Horn rules and description logics in CARIN. Artif Intell. 1998;104(1–2):165–209.MathSciNetCrossRefzbMATHGoogle Scholar
  13. 13.
    Pérez-Urbina H, Horrocks I, Motik B. Efficient query answering for OWL 2. In: Proceeding of the 8th internaional semantic web conference (ISWC). Volume 5823 of lecture notes in computer science. Springer; 2009. p. 489–504.Google Scholar
  14. 14.
    Poggi A, Lembo D, Calvanese D, De Giacomo G, Lenzerini M, Rosati R. Linking data to ontologies. J Data Semant. 2008;X:133–73.Google Scholar
  15. 15.
    Rosati R, Almatelli A. Improving query answering over DL-Lite ontologies. In: Proceeding of the 12th international conference on the principles of knowledge representation and reasoning (KR). Toronto; 2010. p. 290–300.Google Scholar

Authors and Affiliations

  1. 1.Research Centre for Knowledge and Data (KRDB)Free University of Bozen-BolzanoBolzanoItaly
  2. 2.Dip. di Ingegneria Informatica Automatica e Gestionale Antonio RubertiSapienza Università di RomaRomeItaly
  3. 3.Dip. di Ingegneria Informatica Automatica e Gestionale Antonio RubertiSapienza Università di RomaRomeItaly
  4. 4.Dip. di Ingegneria Informatica Automatica e Gestionale Antonio RubertiSapienza Università di RomaRomeItaly
  5. 5.Dip. di Ingegneria Informatica Automatica e Gestionale Antonio RubertiSapienza Università di RomaRomeItaly

Section editors and affiliations

  • Kevin Chang
    • 1
  1. 1.Department of Computer ScienceUniversity of Illinois at Urbana-ChampaignUrbanaUSA